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Neural networks for perception / 1 Human and machine perception.

Author: Harry Wechsler
Publisher: San Diego u.a. : Acad. Press, 1992.
Series: Neural networks for perception / ed. by Harry Wechsler, vol. 1
Edition/Format:   Print book : EnglishView all editions and formats
Summary:

This volume, part of a series, explores recent research in neural networks in terms of how they have advanced understanding of human and machine perception. Both theoretical and practical aspects are  Read more...

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Document Type: Book
All Authors / Contributors: Harry Wechsler
ISBN: 0127412514 9780127412511
OCLC Number: 165524076
Description: XXI, 520 Seiten : Diagramme.
Contents: Part 1 Human and machine perception: visual cortex - window on the biological basis of learning and memory, L. Cooper; a network model of object recognition in human vision, S. Edelman; a cortically based model for integration in visual perception, F. Finkel, et al; the symmetric organization of parallel cortical systems for form and motion perception, S. Grossbert; the structure and interpretation of neuronal codes in the visual system, B. Richmond and L.M. Optican; self-organization of functional architecture in the cerebral cortex, S. Tanaka; filters versus textons in human and machine texture discrimination, D. Williams and B. julesz; two-dimensional maps and biological vision - representing three-dimensional space, G.L. Zimmerman. Part 2 Machine perception: wisards and other weightless neurons, I. Aleksander; multi-dimensional linera lattice for Fourier and Gabor transforms, multiple-scale Gaussian filtering and edge detection, J. Ben-Arie; aspects of invariant patterns and object recognition, T. Caelli, et al; a neural network architecture for fast on-line supervised learning and pattern recognition, G. Carpenter, et al; neural network approaches to color vision, A. Hurlbert; adaptive sensory-motor co-ordination through self-consistency, M. Kuperstein; finding boundaries in images, J. Malik and P. Perona; compression of remotely sensed images using self-organizing feature maps, M. Manohar and J. Tilton; region growing using neural networks, T. Reed; vision and space-variant sensing, G. Sandini and M. Tistarelli; learning and recognizing three-dimensional objects for multiple views in a neural system, M. Seibert and A. Waxman; hybrid symbolic-neural methods for improved recognition using high-level visual features, G. Towell and J. Shavlik; multiscale and distributed visual representations and mappings for invariant low-level perception, H. Wechsler; symmetry - a context-free cue for foveated vision, Y. Yeshurun, et al; a neural network for motion processing, Y.T. Zhou and R. Chellappa.
Series Title: Neural networks for perception / ed. by Harry Wechsler, vol. 1
Responsibility: ed. by Harry Wechsler.
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